Superlinked, a solution for turning complex data into vector embeddings, has raised $9.5 million in seed funding led by Index Ventures. Superlinked aims to fill the gap between data and vector databases by providing a compute framework that turns all kinds of data into vector embeddings, making it easier for companies to build machine learning-powered software on top of their complex data.
Vectors power online services like hailing cabs, searching for videos and scrolling through shopping feeds. Many enterprises want to upgrade their analytics, search and recommendation systems to use vectors. In ML-powered information retrieval, the objectives and underlying enterprise data are typically too complex to be vectorized by pre-trained large language models. Superlinked addresses this challenge with its framework that optimizes retrieval control, quality and efficiency in real time.
Superlinked has partnered with tech companies including MongoDB, Redis, Dataiku and Starburst on integrations to expand its reach and capabilities. The company will use its new funding to scale and expand its product capabilities.
